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Statistical study of surface texture and chip formation during turning of AISI 1020 steel: Emphasis on parameters Rsk, Rku, and Rk family and on the chip thickness ratio.

Authors :
Talibouya Ba, Elhadji Cheikh
Martins, Paulo Sérgio
Dumont, Marcello Rosa
Source :
International Journal of Advanced Manufacturing Technology. Aug2022, Vol. 121 Issue 11/12, p8257-8283. 27p.
Publication Year :
2022

Abstract

Turning is recognized as one of the main manufacturing processes. Feed and cutting depth are investigated by researchers who aim to continuously improve this process. Faced with sustainability challenges, "greener" manufacturing engineering is sought, using statistical methods and machining techniques with minimal or no use of cutting fluid. Generally, roughness quantifies the quality of the machined surface, an important property in tribology. Classical amplitude parameters are insufficient to determine functional properties and are necessary to associate them with more significant ones. Chip formation also influences surface quality, as it is related to the interaction at the chip/tool interface. This study investigated the influence of the feed rate and cutting depth on the Rq, Rsk, Rku, Rk, Rpk and Rvk roughness parameters, and the chip thickness ratio during longitudinal dry turning of AISI 1020 steel. Trend measurements, a normality test, factorial analysis of variance and linear correlation were used in the methodology. Results showed predominant influence and correlation of the feed on the roughness parameters and the chip thickness ratio compared to the cutting depth. The analysis performed on the insert rake surface led to the hypothesis that the chip breaker geometry provides changes in chip deformation as the cutting depth increases. Through linear and polynomial trend lines drawn on the graphs, it was found that the roughness and the chip thickness ratio have a positive correlation with the feed, but in different proportions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
121
Issue :
11/12
Database :
Academic Search Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
158564256
Full Text :
https://doi.org/10.1007/s00170-022-09919-1